In recent years the biometric system lacks in security due to fraudulent access. Old systems relayed on Multi-Spectral Imaging (MSI) for security which is found to be ineffective. The advanced technology in the biometric system to improve security is Image Quality Assessments (IAQ). In the previous system, the Multi-Spectral Imaging (MSI) was implemented in which the usual digital protection mechanisms and enhanced security systems are not effective. A novel software based biometric detection system is proposed here to detect the fraudulent biometric access attempts. It is used to enhance the security of biometric recognition systems. In this system from the original image, 30 image quality features are extracted, the same acquired for authentication purposes. Among various biometric recognition, finger recognition, iris recognition and face recognition are presented by using image quality assessment technique.
Digital payment methods have become increasingly prevalent in recent years, revolutionizing the way transactions are conducted. Understanding the factors that drive the adoption of digital payment platforms and the challenges encountered by younger consumers is crucial for businesses and policymakers alike. This research utilizes a mixed-methods approach, combining quantitative surveys and qualitative interviews to gather comprehensive data. The study identifies the motives behind the adoption of digital payment, including convenience, security, and peer influence, while also exploring the barriers and challenges faced by Generation Z and Millennials, such as trust issues and technological complexities. By analysing the findings, this research aims to provide valuable insights and recommendations for businesses and policymakers to better cater to the needs and preferences of these consumer segments.
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